June 26, 2019

4 Ways Big Data is Transforming Healthcare Analytics

Dave Levin, MD

Chief Medical Officer

Information and data analytics are the driving force behind modern innovation. We can’t think of a better way to use data analytics than to save lives and improve healthcare. One of the fastest growing data stores is patient data, and the information doctors and hospitals collect about diseases or drugs. This data flows in at a constant rate, and the sheer volume of such data that already exists is overwhelming.

The big data and data analytics in healthcare market is poised to reach over $68.75 billion by the year 2025. That number alone underscores the importance of finding ways to utilize healthcare data and bring its power to bear on the problems facing those charged with patient care and medical research.

4 Key Ways Big Data is Transforming Healthcare Analytics

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To understand how analytics and big data are making an impact, we first need to understand what they mean to the industry. Just a couple of decades ago, looking at data required hundreds, possibly thousands, of hours of time, not to mention the people required to find the data and put it into a human-readable form. Big data has changed that for nearly everyone in some significant ways including:

  • Patient health tracking and Identifying high-risk patients
  • Cost reduction
  • Improving patient engagement
  • Closing population health gaps

1. Patient Health Tracking and Identifying High-Risk Patients ###

Big data analytics allow researchers and providers to see or visualize a patient’s health throughout their life. Tracking patient health leads to identifying potential problems and risks earlier, which could vastly improve the patient’s overall health over time.

2. Reducing Costs to Providers and Patients

Since everything is recorded on a computer today, visualizing data and finding financial waste no longer requires an army of accountants or financial analysts. For instance, hospitals and providers can use analytics to predict when patients in their area may need more care, such as during flu season. Predictive analysis enables providers to more accurately predict staffing needs and ensure that adequate supplies are on hand to meet demand. 

3. Improving Patient Engagement

Patient engagement is a vital and rapidly growing part of healthcare. Guiding patients toward using wearable technology and other health tracking devices can unlock more valuable patient health data, giving providers a better picture of the patient’s current health status and identifying areas where the patient might improve their lifestyle in favor of better overall health.

4. Improving Population Health

Data-driven healthcare is the key to improving population health. According to a CMS blog post, a data-informed approach is the best way to improve the overall health of minority populations like Hispanic Americans by providing better insights that help providers understand their patients and identifying disparities in the quality of care. 

All of these points are ways that big data has improved healthcare analytics. Big data is the driving force behind moving from pen and paper analytics to more comprehensive visualizations of an individual patient’s health or a community’s or population’s health. However, as healthcare organizations rely on a variety of disparate systems to collect and analyze patient data, interoperability remains a prominent challenge as the industry seeks to better leverage big data to improve health outcomes. 

Looking into the Future of Healthcare Analytics!

Looking into the Future of Healthcare Analytics

While big data has already transformed healthcare and improved patient health in many significant ways, there is much more to come in the future. Data scientist and providers are looking at big data the same way they once viewed breakthrough medications. After all, understanding patients is the best way to make sure they get the care they need, and modern healthcare analytics provides a deeper understanding of patients and populations than ever possible before. 

According to section 3025 of the Affordable Care Act, the Secretary of the Department of Health and Human Services is charged with setting up a value-based purchasing program for Medicare, called the Hospital Readmission Reduction Program (HRRP). Part of this program’s goal is to reduce hospital visits by better understanding a patient’s health.

Analytics based on big data help hospitals and providers see the bigger picture of hospital admissions, which allows them to find problems like excessive readmissions, identify contributing factors, and implement new practices to reduce similar outcomes in the future. This information is used to grade a hospital’s performance, as well. By looking at patient histories and hospital performance, we can find the gaps in care and transform healthcare, thus improving care delivery as a whole.

Data stores will grow, and the tools we use to analyze them will improve almost weekly if we base this assumption on current trends. Obviously, the data stores are growing by the minute, and plenty of talented programmers and data technicians are working on big ideas for the next step in big data and health analytics. Healthcare organizations and researchers alike must embrace clinical data management best practices to identify relevant data, verify data integrity and quality, and standardize data collection and monitoring processes to reduce data collection and reporting errors. 

That said, many companies like Microsoft have released tools that allow people without coding skills to build apps around looking at big data. Granted, you’re better off employing trained professionals to manage your analytics, but tools like those from Microsoft reduce the time it takes to create apps and make housing big data safer and easier.

The Problems Facing Healthcare Analytics

With so much data available from a vast number of collection sources, privacy is and will be a critical pivot point in how we use big data and what data we can legally use for analytics. Possibly half of the ethics violations and concerns we see today revolve around personal data and how it gets used. Nothing highlights this problem more than the issues Facebook faced in Germany recently.

It’s hard to define a line that we might cross where our efforts to improve healthcare violate privacy laws and ethics. We know the difference between right and wrong, and we understand patient data must be protected, but the legal side of this issue is struggling to provide clear guidelines and laws that fairly govern big data usage.

Big data is transforming healthcare analytics and will continue to help providers render better care. However, the need for better tools is dire, and healthcare is struggling under a distinct lack of data scientists qualified to help organizations leverage big data and healthcare analytics both safely and effectively. Hopefully, the future will see more professionals building careers around healthcare analytics to help providers transform healthcare as a whole and continue to improve patient health.

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